The Advocacy  Institute Logo
image Search   Contact UsDonatefacebookfacebook

 About UsProjectsServicesResourcesAdvocate AcademyAdvocacy in ActionHome page

improving the lives of people with disabilities


SLD Identification: An Analysis of State Policies

Edward K. Schultz
Assistant Professor of Special Education, Midwestern State University

Tammy L. Stephens
Assistant Professor of Special Education, Texas Woman’s University

The Advocacy Institute :: Experts on the Record
Listen to our audio interview with the authors of this analysis!
(17 minutes, opens in Media Player )

The reauthorization of the Individuals with Disabilities Education Improvement Act (IDEA; 2004) has resulted in many changes in the field of special education; specifically in the eligibility criteria used to determine the presence of a specific learning disability. Results indicate variability among the states regarding eligibility with all states using response to intervention and the majority of states allowing the use of various discrepancy models.

The 2004 Individuals with Disabilities Education Improvement Act (IDEA; 2004) and subsequent regulations published August 2006 have significantly changed the way students suspected of having specific learning disabilities (SLD) are identified and found eligible for special education. Specifically, under IDEA (2004), school districts are no longer required to use a discrepancy model when determining eligibility, but instead, may use alternative means (e.g., response-to-intervention or processing deficit approaches) to identify students.

When identifying students as having a learning disability, local education agencies (LEAs) must use criteria set forth by their respective state education agencies (SEAs). While consistencies in the identification of specific learning disabilities may occur within states, considerable differences occur in the identification process between states (Ahearn, 2003; Ahearn, 2008; Zirkel & Krohn, 2008). To further complicate matters, the lack of consensus concerning the operational definition of SLD , selecting the most effective methods of identification (Flanagan, Ortiz, Alfonso & Dynda, 2006; Fletcher, Denton, & Francis, 2005; Fletcher, Francis, Morris, & Lyon, 2005; Kavale, Holdnack, & Mostert, 2005; Kavale, Kauffman, Bachmeier, & LeFever, 2008; Van den Broek, 2002) continues to be the topic of significant debate. This article will describe the contemporary approaches to specific learning disability identification and the eligibility criteria selected by each state.

Contemporary Approaches to Identification
Current identification approaches can be classified into three broad models: (a) discrepancy approaches, (b) response-to-intervention (RTI) and problem solving approaches, and (c) the processing deficit approaches.

Discrepancy Approach
Prior to the IDEA regulatory changes in 2006, mathematical approaches, specifically the discrepancy model, have been the primary approach to identification of specific learning disabilities. (Baer, 2000; Dombrowski, Kamphaus, & Reynolds, 2004; Frankenberger & Fronzaglio, 1991; Kavale, 2002; Meyer, 2000). According to IDEA (2004), states are not allowed to “require the use of severe discrepancy between intellectual ability and achievement,” however, it remains permissible to use along with RTI and “other alternative research-based procedures (IDEA, 20 U.S.C.§1414 (b)(6)(A).” The underlying concept of discrepancy approaches is that specific learning disabilities are operationalized as “unexpected underachievement” (Dombrowski et al., 2004; Kavale, 2002; Proctor & Prevatt, 2003).

Response- to- Intervention (RTI) is a multi-tiered prevention model of support that delivers interventions and services at increasing levels of intensity based on the response of the student (Bradley, Danielson, & Doolittle, 2007).This approach is dependent upon a systematic process that includes: (a) the application of scientific, evidence-based interventions delivered in general education, (b) monitoring the progress of students response to these interventions, and (c) the use of RTI data to make informed instructional decisions. While many of the concepts of RTI have been familiar to educators for years, RTI gained legal status when it was included in Public Law 108-446, the reauthorized Individuals with Disabilities Education Improvement Act 2004 (Bradley, et al., 2007)

Processing Deficit Approaches
Identification based on processing deficits approaches have primarily focused on operationalizing the federal definition of SLD and the processes linked to reading such as “phonological processing.” According to Ahearn (2003), there is some agreement among professionals that certain psychological processing problems interfere with a student’s learning such as limitations in working memory capacity, phonological processing deficits, and auditory perception. Currently there is not widespread acceptance that processing deficit approaches are a viable method of identifying SLD (Bradley, et al., 2002, p. 797). However, examining processing deficits has given meaning to the most salient component of the federal definition of SLD?a disorder in one or more of the basic psychological processes and has resulted in some states using this approach as an allowable methodology (Fiorello, Hale, & Snyder, 2006; Flanagan et al., 2006; Kavale et al., 2005).

Confusion and debate regarding the operational definition of SLD has resulted in a lack of consensus regarding the use of one specific eligibility model across the United States. Specifically, an assortment of eligibility models defined within this article are currently being utilized within school districts throughout the United States. Therefore, the purpose of this study is to identify which eligibility models are most prominently used within LD eligibility determination since the reauthorization of IDEA (2004).

Data were collected by accessing each state’s education website and locating their respective special education rules and regulations. The following procedures were applied: (a) the Special Education Department from each of the fifty states’ Department of Education was accessed via internet searches, (b) the special education rules and regulations for each state were downloaded from the educational site, (c) using a checklist to organize eligibility models, the two researchers reviewed each states’ rules and regulations and (d) the results were analyzed and compiled within a table.


Continue to Allow the Use of the Discrepancy Model
The majority of the states allow for the continued use of the discrepancy model when determining SLD eligibility. Specifically, thirty-nine (n = 39) states indicated that local education agencies may continue to utilize the discrepancy model as an option of identification. Of the thirty-nine states which continue to allow the use of a severe discrepancy model, twenty-nine (n = 29) allow for the use of a severe discrepancy and/or RTI. Furthermore, ten (n = 10) allow for the use of a severe discrepancy model, RTI, and/or an alternative research-based method of identification.

Elimination of the Discrepancy Model
Of the fifty states analyzed, eleven states (n = 11) were identified as prohibiting the use of the discrepancy model for eligibility. Instead of allowing the use of the discrepancy model, the states vary in the type of criteria they allow. For example, Indiana (Indiana State Board of Education, 2008) prohibits the use of the discrepancy model and instead allows the use of RTI and/or the use of a research-based method which assesses patterns of strengths and weaknesses between cognitive abilities and achievement.

Explicit Mention of Professional Judgment
Many states have placed increased emphasis on the use of the “professional judgment” of educational personnel when determining eligibility. Specifically, Arizona, Georgia, and New Mexico explicitly mention the implementation of “professional judgment” within their state rules and regulations. According to the Georgia state regulations, the ultimate determination of SLD eligibility is determined through professional judgment using multiple supporting evidences to include data collected from norm-referenced assessments and/or benchmarks, information from the student’s teacher regarding classroom routines and instruction, information provided regarding supplementary instruction, and information obtained from parents and school records.

Additional Criteria for Specific Learning Disability Eligibility
Several states allow assessment personnel to use a “research-based alternative eligibility method” when determining eligibility. Of the fifty states, twenty-one (N = 21) allow for the use of an alternative method of eligibility, generally by determining if a student exhibits a pattern of strengths and weaknesses and/or examining specific areas of cognitive processes that interfere with learning. The following states will be briefly described to illustrate these approaches: Indiana and Texas.

Indiana’s Special Education rules (2008) described SLD as “neurological in origin” and allow “intellectual development that is determined by the group to be relevant to the identification of a specific learning disability” to be used as evidence to support their findings. Specific cognitive processes that are linked to specific academic skills are assessed. For example, nonverbal problem solving, working and long-term memory, processing speed, and attention are assessed when a student has difficulty in math. In a similar fashion, the commissioner’s rules concerning special education in Texas (2008) permits examining a pattern of strengths and weaknesses and examining specific areas of cognitive processing and linking them to areas of achievement as a method of identification. In addition to not achieving adequately on age or grade level achievement standards, a student may be considered learning disabled if he or she: (II) exhibits a pattern of strengths and weaknesses in performance, achievement, or both relative to age, grade-level standards, or intellectual ability, as indicated by significant variance among specific areas of cognitive function, such as working memory and verbal comprehension, or between specific areas of cognitive function and academic achievement (p.4).


The reauthorization of the Individuals with Disabilities Education Improvement Act (IDEA, 2004) has resulted in new guidelines for eligibility in the area of specific learning disability. State education agencies have been charged with the responsibility of interpreting federal regulations and setting guidelines for local education agencies to follow when determining eligibility. Initial analyses of state guidelines indicate much variability continues to exist in the eligibility models being used across the fifty states. In adherence to federal guidelines, all state education agencies allow for the use of a response-to-intervention model in some form. Additionally, the majority of the states continue to allow for the use of a discrepancy model as an allowable methodology.

US Dept. of Education Guidance to States on RtI:

On January 21 2011, the Office of Special Education Programs at the U.S. Dept. of Education issued a memorandum to State Directors of Special Education regarding the use of RtI to delay-deny an evaluation for eligibility under the IDEA.


Ahearn, E.M. (2003). Specific learning disability: Current approaches to identification and
proposals for change. Retrieved October 3, 2008 from

Ahearn, E.M. (2008). State eligibility requirements for specific learning disabilities. Retrieved
October 3, 2008 from

Anthony, J.L., & Francis, D.J. (2005). Development of phonological awareness. Current
Directions in Psychological Science, 14, 255-259.

Baer, R.D. (2000). Issues in severe discrepancy measurement: A technical assistance paper for
special educators. Logan, UT: Utah State University, Center for Persons with Disabilities.

Bradley, R., Danielson, L., & Hallahan, D. (2002). Identification of learning disabilities:
Research to practice. Mahwah, NJ: Lawrence Erlbaum.

Bradley, R., Danielson, L., & Doolittle, J. (2007). Responsiveness to intervention: 1997-2007.
Teaching Exceptional Children, 39, 8-12.

Dombrowski, S. C., Kamphaus, R.W., & Reynolds, C.R. (2004). After the demise of the
discrepancy: Proposed learning disabilities diagnostic criteria. Professional Psychology: Research and Practice, 35, 364-372.

Fiorello, C.A., Hale, J.B., & Snyder, L.E. (2006). Cognitive hypothesis testing and response to
intervention for children with reading problems. Psychology in the Schools, 43, 835-853.

Flanagan, D.P., ORTIz. S.O., Alfonso, V.C., & Dynda, A.M. (2006). Integration of response to
intervention and norm-referenced tests in learning disability identification: Learning from the tower of Babel. Psychology in the Schools, 43, 807-825.

Fletcher, J.M., Denton, C., & Francis, D.J. (2005). Validity of alternative approaches for the
identification of learning disabilities: Operationalizing unexpected achievement. Journal of Learning Disabilities, 38, 545-552.

Fletcher, J.M., Francis, D.J., Morris, R.D., & Lyon, G.R. (2005). Evidence-based assessment of
learning disabilities in children and adolescents. Journal of Clinical Child and Adolescent Psychology, 34, 506-522.

Frankenberger, W., & Fronzaglio, K. (1991). A review of states’ criteria and procedures for
identifying children with learning disabilities. Journal of Learning Disabilities, 24, 495-500.

Individuals with Disabilities Education Improvement Act of 2004 (IDEA), Pub.L.No.108-446,
118 Stat. 2647 (2004), [Amending 20 U.S.C. § § 1400 et seq.].

Kavale, K.A. (2002). Discrepancy models in the identification of learning disability. In R. Bradley, L. Danielson, & D.P. Hallahan (Eds.), Identification of learning disabilities: Research to practice (pp. 369-426). Mahwah, NJ: Erlbaum.

Kavale, K.A., Holdnack, J.A., & Mostert, M.P. (2005). Responsiveness to intervention and the
identification of specific learning disability: A critique and alternative proposal. Learning Disability Quarterly, 28-2-16.

Kavale, K.A., Kauffman, J.M., Bachmeier, R. J., & LeFever, G.B. (2008). Response-to-
intervention: Separating the rhetoric of self congratulation from the reality of specific learning disability identification. Learning Disability Quarterly, 31, 135-150.

Meyer, M.S., (2000). The ability-achievement discrepancy: Does it contribute to an
understanding of learning disabilities. Educational Psychology Review, 12, 315-337.

Proctor, B., & Prevatt, F. (2003). Agreement among four models used for diagnosing learning
disabilities. Journal of Learning Disabilities, 36, 459-467.

Van den Broek, W. (2002). The misconception of the regression-based discrepancy
operationalization in the definition and research of learning disabilities. Journal of
Learning Disabilities, 35, 194-204.

Zirkel, O.A., & Krohn, N. (2008). RTI after IDEA: A survey of state laws. Teaching Exceptional
Children, 40, 71-73.

About Us | Projects | Services | Resources | Advocacy in Action | Contact Us | Donate | Home

Copyright 2001-2024 The Advocacy Institute